{"id":"W4411449886","doi":"10.1145/3729353","title":"LookAhead: Preventing DeFi Attacks via Unveiling Adversarial Contracts","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ACM on software engineering.","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Adversarial system; Computer science; Database transaction; Focus (optics); Software deployment; Computer security; Artificial intelligence; Code (set theory); Semantics (computer science); State (computer science); Machine learning; Database; Programming language; Software engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003137972,0.0001623835,0.0002043501,0.0001589559,0.000134802,0.00004699087,0.002952957,0.0001566706,0.000001559248],"category_scores_gemma":[0.002199876,0.0001377712,0.0001063522,0.000680963,0.00004634655,0.0001546138,0.001190702,0.0003626265,0.000004300247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005557789,"about_ca_system_score_gemma":0.00003616752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007944622,"about_ca_topic_score_gemma":6.392202e-7,"domain_scores_codex":[0.9989306,0.000002777783,0.0002727518,0.0003422509,0.0001857396,0.0002659345],"domain_scores_gemma":[0.998749,0.000179857,0.000146261,0.0007243184,0.0001647013,0.00003583413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005454895,0.0005688653,0.03544559,0.0007714923,0.0003465092,0.000002200052,0.0008886644,0.003556125,0.02668519,0.8619467,0.008272897,0.06146123],"study_design_scores_gemma":[0.003312068,0.0002950798,0.04611555,0.001798888,0.0001854515,0.00005127464,0.00009716743,0.1697613,0.5980831,0.1393781,0.03933589,0.001586114],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5874726,0.0003640179,0.4052383,0.003340648,0.0009145123,0.0007051082,0.000004014376,0.001423673,0.0005371361],"genre_scores_gemma":[0.890887,0.000005270803,0.1087786,0.0001497344,0.00003783951,0.00004459537,3.230474e-7,0.00001048078,0.0000861778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7225686,"threshold_uncertainty_score":0.5618148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005683394962144602,"score_gpt":0.2175159818541883,"score_spread":0.2118325868920437,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}